Predictive Model Cooking Method for Precise Rice Texture Control
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Solution Overview
Problem
Existing cooking appliances, such as rice cookers, lack precision in achieving desired textures for cooked rice and other grains due to limitations in their cooking programs, which fail to accurately control firmness, stickiness, gloss, elasticity, and adhesiveness.
Innovation Solution
A method that uses predictive mathematical models based on the initial water-to-food ratio and soaking time/temperature to automatically determine and adjust cooking parameters, allowing for precise control of organoleptic properties like firmness and stickiness, by analyzing a sample food and applying hydro-thermal cycles tailored to specific grain varieties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional cooking programs with fixed water ratios and heating cycles are used, then the cooking process is simple to operate, but the texture precision (firmness, stickiness, gloss) cannot be achieved
Solution Approach 1:
The patent applies parameter changes by using a predictive mathematical model that dynamically adjusts cooking parameters (heating power, soaking time, water ratio) based on the desired texture output. The model transforms the relationship between cooking parameters and texture parameters, allowing precise control of firmness, stickiness, and gloss by changing the underlying parameters in the cooking process rather than using fixed programs.
Solution Approach 2:
The patent implements feedback through the predictive mathematical model that continuously relates cooking parameters to texture outcomes. The system uses the model to predict the resulting texture based on selected cooking parameters, and adjusts parameters iteratively to achieve the desired texture precision, creating a closed-loop control system that enhances manufacturing precision.
2Manufacturing precision
If multiple texture parameters (firmness, stickiness, gloss, elasticity, adhesiveness) are controlled precisely, then the cooking quality is improved, but the control system becomes more complex
Solution Approach 1:
The patent applies self-service by enabling the predictive mathematical model to automatically determine the optimal cooking parameters and hydro-thermal cycle based on the user's desired texture. The system performs self-calculation and self-adjustment of cooking conditions without requiring manual intervention or complex user input, thereby maintaining ease of operation while achieving precise control of multiple texture parameters.
Solution Approach 2:
The patent uses parameter changes to transform multiple texture control requirements into a simplified user interface. By changing the internal representation from multiple independent texture controls to a single predictive model that handles all parameters simultaneously, the system maintains operational simplicity while achieving precise control over firmness, stickiness, gloss, elasticity, and adhesiveness.
3Manufacturing precision
If the water-to-food ratio is adjusted to control texture, then the texture parameter precision is improved, but the cooking time and energy consumption increase
Solution Approach 1:
The patent applies preliminary action by incorporating a soaking phase before the main cooking process, during which the food is pre-treated with water at controlled ratios and temperatures. This preliminary action prepares the food structure to achieve desired texture more efficiently during the subsequent cooking phase, reducing total cooking time while maintaining texture precision. The predictive model optimizes the soaking duration and water ratio to prevent excessive time consumption.
Solution Approach 2:
The patent uses dynamics by implementing a dynamic hydro-thermal cycle that continuously adjusts heating power, water addition, and soaking time based on the predictive mathematical model's calculations. Rather than using static fixed-ratio cooking, the system dynamically modifies cooking conditions in real-time to achieve optimal texture precision while minimizing cooking time and energy consumption through adaptive parameter adjustment.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables precise control over the texture of cooked grains, ensuring consistency with user preferences by optimizing the cooking process through predictive models, enhancing the precision of texture parameters like firmness and stickiness.
Implementation Method 1
a heating system arranged in the base body to heat the food and water placed in the cooking enclosure
Implementation Method 2
a pressure regulation system arranged in the base body to regulate a pressure in the cooking enclosure during a cooking of the food and water placed in the cooking enclosure
Data Source
Figure 1~2
Figure 3~4C
Figure 5~8
AI summary
The present invention relates to a method for cooking food, particularly rice, in the presence of water in a cooking chamber, wherein a cooking program for the food is automatically determined and/or offered and/or made selectable by the user, at least in part based on a mathematical model predictive of the behavior of at least one organoleptic parameter of the food as a function of at least an initial water/food ratio in the cooking chamber, and a desired value for said parameter.